{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  GP latent function inference"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook uses GP to infer a latent function $\\lambda(x)$, which parameterises the exponential distribution:\n",
    "$$y \\sim Exponential(\\lambda),$$\n",
    "where:\n",
    "$$\\lambda = exp(f) \\in (0,+\\infty)$$\n",
    "is a GP link function, which transforms the latent gaussian process variable:\n",
    "$$f \\sim GP \\in (-\\infty,+\\infty).$$\n",
    "\n",
    "In other words, given inputs $X$ and observations $Y$ drawn from exponential distribution with $\\lambda = \\lambda(X)$, we want to find $\\lambda(X)$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "import torch\n",
    "import pyro\n",
    "import gpytorch\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "pyro.enable_validation(True)\n",
    "\n",
    "%matplotlib inline\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#here we specify a 'true' latent function lambda\n",
    "scale = lambda x: np.sin(2*np.pi*1*x)+1 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Generate Synthetic Data\n",
    "\n",
    "In the next cell, we generate synthetic data from the generative process described above, using $sin(2\\pi x) + 1$ as the true scale function. On the domain $[0, 1.0]$, we expect smaller $x$ values to give rise to y values from exponential distributions with larger scale parameters. We plot samples from the true exponential distribution at each training x value we generate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jake.gardner/anaconda3/lib/python3.7/site-packages/matplotlib/figure.py:445: UserWarning: Matplotlib is currently using module://ipykernel.pylab.backend_inline, which is a non-GUI backend, so cannot show the figure.\n",
      "  % get_backend())\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# here we generate some synthetic samples\n",
    "NSamp = 100\n",
    "\n",
    "X = np.linspace(0,1,NSamp) \n",
    "\n",
    "fig, (lambdaf, samples) = plt.subplots(1,2,figsize=(10,3))\n",
    "\n",
    "lambdaf.plot(X,scale(X))\n",
    "lambdaf.set_xlabel('x')\n",
    "lambdaf.set_ylabel('$\\lambda$')\n",
    "lambdaf.set_title('Latent function')\n",
    "\n",
    "Y = np.zeros_like(X)\n",
    "for i,x in enumerate(X):\n",
    "    Y[i] = np.random.exponential(scale(x), 1)\n",
    "samples.scatter(X,Y)\n",
    "samples.set_xlabel('x')\n",
    "samples.set_ylabel('y')\n",
    "samples.set_title('Samples from exp. distrib.')\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#convert numpy data to tensors (optionally on GPU)\n",
    "train_x = torch.tensor(X).float()#.cuda()\n",
    "train_y = torch.tensor(Y).float()#.cuda()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Define Pyro variational GP model\n",
    "\n",
    "In GPyTorch, a pyro variational GP model is identical to a standard variational GP model, except (1) it extends `PyroVariationalGP` instead of `AbstractVariationalGP`, and (2) it defines a `name_prefix`, which is used in `pyro.sample` and `pyro.module` calls.\n",
    "\n",
    "In general, a `PyroVariationalGP` model also defines a `model` and `guide`. However, for this latent function example, we are able to use the default `model` and `guide` defined in the base class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "class PVGPRegressionModel(gpytorch.models.PyroVariationalGP):\n",
    "    def __init__(self, train_x, train_y, likelihood, name_prefix=\"mixture_gp\"):\n",
    "        # Define all the variational stuff\n",
    "        variational_distribution = gpytorch.variational.CholeskyVariationalDistribution(\n",
    "            num_inducing_points=train_x.numel()\n",
    "        )\n",
    "        variational_strategy = gpytorch.variational.VariationalStrategy(\n",
    "            self, train_x, variational_distribution\n",
    "        )\n",
    "        \n",
    "        # Standard initializtation\n",
    "        super(PVGPRegressionModel, self).__init__(variational_strategy, likelihood, num_data=train_x.numel())\n",
    "        self.likelihood = likelihood\n",
    "        \n",
    "        # Mean, covar\n",
    "        self.mean_module = gpytorch.means.ConstantMean()\n",
    "        \n",
    "        #we specify prior here\n",
    "        prior_rbf_length = 0.3 \n",
    "        lengthscale_prior = gpytorch.priors.NormalPrior(prior_rbf_length, 1.0) #variance does not matter much\n",
    "        \n",
    "        self.covar_module = gpytorch.kernels.ScaleKernel(\n",
    "            gpytorch.kernels.RBFKernel(lengthscale_prior=lengthscale_prior),\n",
    "        )\n",
    "        \n",
    "        # Initialize lengthscale and outputscale to mean of priors\n",
    "        self.covar_module.base_kernel.lengthscale = lengthscale_prior.mean\n",
    "        #self.covar_module.outputscale = outputscale_prior.mean\n",
    "\n",
    "    def forward(self, x):\n",
    "        mean = self.mean_module(x)  # Returns an n_data vec\n",
    "        covar = self.covar_module(x)\n",
    "        return gpytorch.distributions.MultivariateNormal(mean, covar)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Define the Likelihood\n",
    "\n",
    "The primary \"new\" thing we need to define for this sort of latent function inference is a new likelihood, `p(y|f)`. In this case, the mapping is `p(y|f) = Exponential(exp(f))`. See the docs for `gpytorch.likelihoods.Likelihood` for more information on what each method does."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torch import Tensor\n",
    "from typing import Any\n",
    "from gpytorch.likelihoods.likelihood import Likelihood\n",
    "from gpytorch.distributions import MultivariateNormal, base_distributions\n",
    "from gpytorch.utils.deprecation import _deprecate_kwarg_with_transform\n",
    "\n",
    "class InfTheta_ExpDist_Likelihood(Likelihood):\n",
    "    def __init__(self, noise_prior=None, noise_constraint=None, batch_shape=torch.Size(), **kwargs: Any):\n",
    "        batch_shape = _deprecate_kwarg_with_transform(\n",
    "            kwargs, \"batch_size\", \"batch_shape\", batch_shape, lambda n: torch.Size([n])\n",
    "        )\n",
    "        super(Likelihood, self).__init__()\n",
    "        self._max_plate_nesting = 1\n",
    "\n",
    "    def expected_log_prob(self, target: Tensor, input: MultivariateNormal, *params: Any, **kwargs: Any) -> Tensor:\n",
    "        mean, variance = input.mean, input.variance\n",
    "        theta = self.gplink_function(mean)\n",
    "        res = - theta * target + theta.log()\n",
    "        return res.sum(-1)\n",
    "    \n",
    "    @staticmethod\n",
    "    def gplink_function(f: Tensor) -> Tensor:\n",
    "        \"\"\"\n",
    "        GP link function transforms the GP latent variable `f` into :math:`\\theta`,\n",
    "        which parameterizes the distribution in :attr:`forward` method as well as the\n",
    "        log likelihood of this distribution defined in :attr:`expected_log_prob`.\n",
    "        \"\"\"\n",
    "        return f.exp()\n",
    "    \n",
    "    def forward(self, function_samples: Tensor, *params: Any, **kwargs: Any) -> base_distributions.Exponential:        \n",
    "        scale = self.gplink_function(function_samples)\n",
    "        return base_distributions.Exponential(scale.pow(-1)) # rate = 1/scale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define the model (optionally on GPU)\n",
    "model = PVGPRegressionModel(train_x, train_y, InfTheta_ExpDist_Likelihood())#.cuda()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Train the Model\n",
    "\n",
    "In the next cell we use Pyro SVI to train the model. See the Pyro docs for general examples of this, as well as our simpler Pyro integration notebooks."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Basic lr for most of parameters: 0.01\n",
      "Iter 50/200 - Loss: 1.15e+02   lengthscale: 0.288\n",
      "Iter 100/200 - Loss: 1.01e+02   lengthscale: 0.285\n",
      "Iter 150/200 - Loss: 94.8   lengthscale: 0.279\n",
      "Iter 200/200 - Loss: 90.7   lengthscale: 0.27\n",
      "CPU times: user 6min 50s, sys: 1min 2s, total: 7min 52s\n",
      "Wall time: 24 s\n"
     ]
    }
   ],
   "source": [
    "# train the model\n",
    "from pyro import optim\n",
    "\n",
    "base_lr = 1./NSamp\n",
    "iter_print = 50\n",
    "\n",
    "print('Basic lr for most of parameters: {}'.format(base_lr))\n",
    "\n",
    "# set learning rates for different hyperparameters\n",
    "def per_param_callable(module_name, param_name):\n",
    "    if param_name == 'covar_module.base_kernel.raw_lengthscale':\n",
    "        return {\"lr\": .1}\n",
    "    elif param_name == 'variational_strategy.variational_distribution.variational_mean':\n",
    "        return {\"lr\": .1}\n",
    "    else:\n",
    "        return {\"lr\": base_lr}\n",
    "\n",
    "# Use the adam optimizer\n",
    "optimizer = optim.Adam(per_param_callable)\n",
    "\n",
    "pyro.clear_param_store() # clean run\n",
    "\n",
    "losses, rbf, means = [], [], []\n",
    "\n",
    "means.append(model.variational_strategy.variational_distribution.\\\n",
    "             variational_mean.detach().cpu().numpy()) #save initial mean\n",
    "\n",
    "def train(num_iter=200):\n",
    "    elbo = pyro.infer.Trace_ELBO(num_particles=256, vectorize_particles=True)\n",
    "    svi = pyro.infer.SVI(model.model, model.guide, optimizer, elbo)\n",
    "    model.train()\n",
    "\n",
    "    for i in range(num_iter):\n",
    "        model.zero_grad()\n",
    "        loss = svi.step(train_x, train_y)\n",
    "        losses.append(loss)\n",
    "        rbf.append(model.covar_module.base_kernel.lengthscale.item())\n",
    "        if not (i + 1) % iter_print:\n",
    "            print('Iter {}/{} - Loss: {:.3}   lengthscale: {:.3}'.format(\n",
    "                i + 1, num_iter, loss,\n",
    "                model.covar_module.base_kernel.lengthscale.item(),\n",
    "            ))\n",
    "            means.append(model.variational_strategy.variational_distribution.\\\n",
    "                         variational_mean.detach().cpu().numpy())\n",
    "        \n",
    "%time train()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jake.gardner/anaconda3/lib/python3.7/site-packages/matplotlib/figure.py:445: UserWarning: Matplotlib is currently using module://ipykernel.pylab.backend_inline, which is a non-GUI backend, so cannot show the figure.\n",
      "  % get_backend())\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 864x144 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# prot loss function and kernel length\n",
    "fig, (loss, kern) = plt.subplots(1,2,figsize=(12,2))\n",
    "loss.plot(losses)\n",
    "loss.set_xlabel(\"Epoch\")\n",
    "loss.set_ylabel(\"Loss\")\n",
    "kern.plot(rbf)\n",
    "kern.set_xlabel(\"Epoch\")\n",
    "kern.set_ylabel(\"Kernel scale parameter\")\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Make Predictions and Plot\n",
    "\n",
    "In the next cell, we get predictions. In particular, we plot the expected scale function learned by the GP, as well as samples drawn from the predictive distribution `p(y|D)`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define test set (optionally on GPU)\n",
    "denser = 2 # make test set 2 times denser then the training set\n",
    "testX = np.linspace(0,1,denser*NSamp)\n",
    "test_x = torch.tensor(testX).float()#.cuda()\n",
    "\n",
    "model.eval()\n",
    "with torch.no_grad():\n",
    "    output = model(test_x)\n",
    "    \n",
    "gplink = model.likelihood.gplink_function\n",
    "\n",
    "\n",
    "# Get E[exp(f)] via f_i ~ GP, 1/n \\sum_{i=1}^{n} exp(f_i). Similarly get sample variances.\n",
    "samples = output.rsample(torch.Size([2048]))\n",
    "F_mean = gplink(samples).mean(0)\n",
    "lower, upper = output.confidence_region()\n",
    "lower = gplink(lower)\n",
    "upper = gplink(upper)\n",
    "\n",
    "with gpytorch.settings.num_likelihood_samples(1):\n",
    "    Y_sim = model.likelihood(model(train_x)).rsample()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jake.gardner/anaconda3/lib/python3.7/site-packages/matplotlib/figure.py:445: UserWarning: Matplotlib is currently using module://ipykernel.pylab.backend_inline, which is a non-GUI backend, so cannot show the figure.\n",
      "  % get_backend())\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualize the result\n",
    "fig, (func, samp) = plt.subplots(1,2,figsize=(12, 3))\n",
    "\n",
    "line, = func.plot(testX, F_mean.detach().cpu().numpy(), label = 'GP prediction')\n",
    "func.fill_between(testX, lower.detach().cpu().numpy(),\n",
    "                upper.detach().cpu().numpy(), color=line.get_color(), alpha=0.5)\n",
    "\n",
    "func.plot(testX,scale(testX), label = 'True latent function')\n",
    "#func.set_xlabel('x')\n",
    "#func.set_ylabel('gp_link(f)')\n",
    "#func.set_title('Latent function')\n",
    "func.legend()\n",
    "\n",
    "# sample from p(y|D,x) = \\int p(y|f) p(f|D,x) df (doubly stochastic)\n",
    "samp.scatter(X, Y, alpha = 0.5, label = 'True train data')\n",
    "samp.scatter(X, Y_sim.cpu().detach().numpy(), alpha = 0.5, label = 'Sample from the model')\n",
    "#samp.set_xlabel('x')\n",
    "#samp.set_ylabel('y')\n",
    "#samp.set_title('Samples from exp. distrib. with scale=gplink(f(x))')\n",
    "samp.legend()\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x216 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualize pdf for y(x)\n",
    "\n",
    "from scipy import stats\n",
    "\n",
    "Nbins = 100\n",
    "\n",
    "latent_sample = gplink(output.sample()).cpu().numpy()\n",
    "\n",
    "img = np.zeros((Nbins,denser*NSamp,3))\n",
    "h = np.linspace(1e-4,5,Nbins)\n",
    "\n",
    "for i, (l, m, t) in enumerate(zip(latent_sample, F_mean, scale(testX)+1e-2)):\n",
    "    img[:,i,0] = stats.expon.pdf(h, scale=m.detach())\n",
    "    img[:,i,1] = stats.expon.pdf(h, scale=l)\n",
    "    img[:,i,2] = stats.expon.pdf(h, scale=t)\n",
    "\n",
    "img = img / np.max(img,axis=0) # normalize pdf, so that max(pdf) = 1\n",
    "\n",
    "num_levels = 15\n",
    "\n",
    "levels = np.exp(np.linspace(1e-4,1,num_levels))\n",
    "levels -= 1\n",
    "levels /= np.max(levels)\n",
    "\n",
    "fig, ax = plt.subplots(1,3, figsize = (15,3))\n",
    "for c, n in enumerate(['Mean prediction', 'Random sample from GP', 'Ground truth']):\n",
    "    ax[c].contour(img[:,:,c], levels = levels)\n",
    "    ax[c].set_yticks(np.linspace(0,Nbins,5))\n",
    "    ax[c].set_yticklabels(np.linspace(0,5,5))\n",
    "    ax[c].set_xticks(np.linspace(0,denser*NSamp,5))\n",
    "    ax[c].set_xticklabels(np.linspace(0,1,5))\n",
    "    ax[c].set_xlabel('x')\n",
    "    ax[c].set_title(n, y=-0.35)\n",
    "ax[0].set_ylabel('y')\n",
    "fig.suptitle('Probability densities for predictions vs. truth', y=1.05, fontsize=14);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
